Safety and Efficacy of Stem Cell Therapy in Patients With Ischemic Stroke
Bibliographic record
Abstract
Stem cell therapy is emerging as a promising treatment strategy to treat patients with stroke. While there are established modes of treatment for stroke patients such as thrombolysis and endovascular intervention, most of the stroke patients frequently end up with major residual deficits or even death. The use of stem cells to treat stroke has been found to be beneficial in the animal models but strict evidence for the same in humans is still lacking. We reviewed 13 clinical trials of stem cell therapy in stroke patients conducted between 2014 and 2020 based on the search using the database PubMed, and the clinical trial registry (www.clinicaltrials.gov). We aimed to assess the safety and efficacy of stem cell treatment in stroke patients who participated in the trials. Quality assessment of the clinical trials revealed a sub-optimal score. We found mixed results regarding the efficacy of stem cells in the treatment of ischemic stroke although we could not do a quantitative analysis of the effect outcomes. Assessment for safety revealed promising results as there were only minor side effects related to cell therapy. Although stem cell therapy seems to be a promising strategy to treat stroke patients in the future, we concluded that the field needs more evidence regarding the safety and efficacy of the use of stem cells in stroke patients before we use them in the clinic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".